CAUSAL MODELING OF WEB-ADVERTISING EFFECTS BY IMPROVING SEM BASED ON DEMATEL TECHNIQUE

Abstract

Causal analysis greatly affects the efficiency of decision-making. Scholars usually adopt structural equation modeling (SEM) to establish a causal model recently. However, statistical data allow researchers to modify the model frequently to arrive at good model fitness, and SEM is often misapplied when the data are merely fitted to an SEM and the theory is then extended from the analytical result based on presumed hypotheses. This paper proposed SEM modified by DEMATEL technique, taking causal model of Web-advertising effects for example. Having revealed that the new model is the one that conforms to actual data and is better than initial model, the results confirm that the DEMATEL technique can be an efficient, complementary, and confident approach for reprioritization of the amended modes in a SEM model. In addition, the most important factor affecting the Web-advertising effects may be found via the modified model, which benefits the manager for making strategic marketing plans.